{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/132600"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/132600","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Analysis of soil compaction and furrow depth from planter row unit","abstract":"In agriculture, the performance of the planter row unit is crucial for specific row-crop operations, such as furrow formation, seed placement, and soil-conditioning during planting. It affects seed spacing and singulation, root growth, emergence, crop health, yield, and field traffic management. This study analyzes how the planter row unit’s operation affects soil compaction, furrow depth, and furrow geometry. The research objectives are divided into two parts. The first part uses X-ray microcomputed tomography (CT) to scan undisturbed soil cores to study soil compaction caused by the tractor and planter row unit soil-engaging components. This technique quantifies soil porosity and compaction by calculating the core's mean cumulative pore volume. The second part employs LiDAR and a single-point laser sensor to measure field furrows under actual operating conditions. This technique assesses the depth and distribution of furrows. X-ray CT can identify and quantify soil beneath furrows compacted by the planter row unit's wheels and other contacting components, thereby reducing soil porosity and compacting soil structure. Differences in planter row-unit configurations, compaction methods, gauge wheel positions, and furrow center offset contribute to distinct compaction patterns. A LiDAR system can continuously and accurately acquire the shape, depth of furrows, and the surface profile. At the same time, a single-point laser sensor can measure furrow depth with minimal error. Both sensors perform reliably, stably, and repeatably under field conditions. However, LiDAR-measured data is more accurate and stable than laser-sensor-measured data. Furrow depth is generally consistent across the entire field furrow, but slight depth deviations occur due to measurement errors and the planter row unit’s operations. The combination of these two methods provides a comprehensive picture of the interaction between the planter and the soil. CT data reveal compaction beneath the soil surface, indicating that the planter row unit Configuration A produces a greater soil compaction. LiDAR and laser sensors can measure a more precise distribution of furrow depth. This combination helps assess how the planter row units affect soil structure and seedbed quality. The findings will help lay the foundation for future work to improve planter design, reduce soil compaction, increase seeding accuracy, and subsequently improve crop emergence.","abstract_html":"In agriculture, the performance of the planter row unit is crucial for specific row-crop operations, such as furrow formation, seed placement, and soil-conditioning during planting. It affects seed spacing and singulation, root growth, emergence, crop health, yield, and field traffic management. This study analyzes how the planter row unit’s operation affects soil compaction, furrow depth, and furrow geometry. The research objectives are divided into two parts. The first part uses X-ray microcomputed tomography (CT) to scan undisturbed soil cores to study soil compaction caused by the tractor and planter row unit soil-engaging components. This technique quantifies soil porosity and compaction by calculating the core's mean cumulative pore volume. The second part employs LiDAR and a single-point laser sensor to measure field furrows under actual operating conditions. This technique assesses the depth and distribution of furrows. X-ray CT can identify and quantify soil beneath furrows compacted by the planter row unit's wheels and other contacting components, thereby reducing soil porosity and compacting soil structure. Differences in planter row-unit configurations, compaction methods, gauge wheel positions, and furrow center offset contribute to distinct compaction patterns. A LiDAR system can continuously and accurately acquire the shape, depth of furrows, and the surface profile. At the same time, a single-point laser sensor can measure furrow depth with minimal error. Both sensors perform reliably, stably, and repeatably under field conditions. However, LiDAR-measured data is more accurate and stable than laser-sensor-measured data. Furrow depth is generally consistent across the entire field furrow, but slight depth deviations occur due to measurement errors and the planter row unit’s operations. The combination of these two methods provides a comprehensive picture of the interaction between the planter and the soil. CT data reveal compaction beneath the soil surface, indicating that the planter row unit Configuration A produces a greater soil compaction. LiDAR and laser sensors can measure a more precise distribution of furrow depth. This combination helps assess how the planter row units affect soil structure and seedbed quality. The findings will help lay the foundation for future work to improve planter design, reduce soil compaction, increase seeding accuracy, and subsequently improve crop emergence.","abstract_has_math":false,"creators":["Yuan, Shaokang"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Agricultural & Biological Engr","degree_department":null,"school":null,"contributors":["Allen, Cody Micheal","Oliveira, Luciano Alves de","Shajahan, Sunoj"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-22T22:25:07Z","subjects":["Planter row unit","Soil compaction","Furrow depth","Furrow geometry","X-ray microcomputed tomography (CT)","LiDAR","Laser sensor","Soil porosity","Seedbed quality","Field measurement","Planter design improvement."],"languages":["en"],"rights":["Copyright 2025 Shaokang Yuan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/132600","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Allen, Cody Micheal","Oliveira, Luciano Alves de","Shajahan, Sunoj"]},{"key":"dc:creator","label":"Author","values":["Yuan, Shaokang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-12","2025-12-11"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural & Biological Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Planter row unit","Soil compaction","Furrow depth","Furrow geometry","X-ray microcomputed tomography (CT)","LiDAR","Laser sensor","Soil porosity","Seedbed quality","Field measurement","Planter design improvement."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Shaokang Yuan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/132600"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In agriculture, the performance of the planter row unit is crucial for specific row-crop operations, such as furrow formation, seed placement, and soil-conditioning during planting. It affects seed spacing and singulation, root growth, emergence, crop health, yield, and field traffic management. This study analyzes how the planter row unit’s operation affects soil compaction, furrow depth, and furrow geometry. The research objectives are divided into two parts. The first part uses X-ray microcomputed tomography (CT) to scan undisturbed soil cores to study soil compaction caused by the tractor and planter row unit soil-engaging components. This technique quantifies soil porosity and compaction by calculating the core's mean cumulative pore volume. The second part employs LiDAR and a single-point laser sensor to measure field furrows under actual operating conditions. This technique assesses the depth and distribution of furrows. X-ray CT can identify and quantify soil beneath furrows compacted by the planter row unit's wheels and other contacting components, thereby reducing soil porosity and compacting soil structure. Differences in planter row-unit configurations, compaction methods, gauge wheel positions, and furrow center offset contribute to distinct compaction patterns. A LiDAR system can continuously and accurately acquire the shape, depth of furrows, and the surface profile. At the same time, a single-point laser sensor can measure furrow depth with minimal error. Both sensors perform reliably, stably, and repeatably under field conditions. However, LiDAR-measured data is more accurate and stable than laser-sensor-measured data. Furrow depth is generally consistent across the entire field furrow, but slight depth deviations occur due to measurement errors and the planter row unit’s operations. The combination of these two methods provides a comprehensive picture of the interaction between the planter and the soil. CT data reveal compaction beneath the soil surface, indicating that the planter row unit Configuration A produces a greater soil compaction. LiDAR and laser sensors can measure a more precise distribution of furrow depth. This combination helps assess how the planter row units affect soil structure and seedbed quality. The findings will help lay the foundation for future work to improve planter design, reduce soil compaction, increase seeding accuracy, and subsequently improve crop emergence.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2026-02-19 without embargo terms","The student, Shaokang Yuan, accepted the attached license on 2025-12-10 at 13:24.","The student, Shaokang Yuan, submitted this Thesis for approval on 2025-12-10 at 13:42.","This Thesis was approved for publication on 2025-12-11 at 14:34.","DSpace SAF Submission Ingestion Package generated from Vireo submission #23124 on 2026-02-19 at 18:30:14"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Analysis of soil compaction and furrow depth from planter row unit"]}]}],"canonical_facts":{"dc:contributor":["Allen, Cody Micheal","Oliveira, Luciano Alves de","Shajahan, Sunoj"],"dc:creator":["Yuan, Shaokang"],"dc:date":["2025-12","2025-12-11"],"dc:description":["In agriculture, the performance of the planter row unit is crucial for specific row-crop operations, such as furrow formation, seed placement, and soil-conditioning during planting. It affects seed spacing and singulation, root growth, emergence, crop health, yield, and field traffic management. This study analyzes how the planter row unit’s operation affects soil compaction, furrow depth, and furrow geometry. The research objectives are divided into two parts. The first part uses X-ray microcomputed tomography (CT) to scan undisturbed soil cores to study soil compaction caused by the tractor and planter row unit soil-engaging components. This technique quantifies soil porosity and compaction by calculating the core's mean cumulative pore volume. The second part employs LiDAR and a single-point laser sensor to measure field furrows under actual operating conditions. This technique assesses the depth and distribution of furrows. X-ray CT can identify and quantify soil beneath furrows compacted by the planter row unit's wheels and other contacting components, thereby reducing soil porosity and compacting soil structure. Differences in planter row-unit configurations, compaction methods, gauge wheel positions, and furrow center offset contribute to distinct compaction patterns. A LiDAR system can continuously and accurately acquire the shape, depth of furrows, and the surface profile. At the same time, a single-point laser sensor can measure furrow depth with minimal error. Both sensors perform reliably, stably, and repeatably under field conditions. However, LiDAR-measured data is more accurate and stable than laser-sensor-measured data. Furrow depth is generally consistent across the entire field furrow, but slight depth deviations occur due to measurement errors and the planter row unit’s operations. The combination of these two methods provides a comprehensive picture of the interaction between the planter and the soil. CT data reveal compaction beneath the soil surface, indicating that the planter row unit Configuration A produces a greater soil compaction. LiDAR and laser sensors can measure a more precise distribution of furrow depth. This combination helps assess how the planter row units affect soil structure and seedbed quality. The findings will help lay the foundation for future work to improve planter design, reduce soil compaction, increase seeding accuracy, and subsequently improve crop emergence.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2026-02-19 without embargo terms","The student, Shaokang Yuan, accepted the attached license on 2025-12-10 at 13:24.","The student, Shaokang Yuan, submitted this Thesis for approval on 2025-12-10 at 13:42.","This Thesis was approved for publication on 2025-12-11 at 14:34.","DSpace SAF Submission Ingestion Package generated from Vireo submission #23124 on 2026-02-19 at 18:30:14"],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/132600"],"dc:language":["en"],"dc:rights":["Copyright 2025 Shaokang Yuan"],"dc:subject":["Planter row unit","Soil compaction","Furrow depth","Furrow geometry","X-ray microcomputed tomography (CT)","LiDAR","Laser sensor","Soil porosity","Seedbed quality","Field measurement","Planter design improvement."],"dc:title":["Analysis of soil compaction and furrow depth from planter row unit"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Agricultural & Biological Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:07Z"}